Adding Data Literacy Skills to Your Toolkit

Developing selected skills in data literacy and management can help librarians make a substantial contribution to the stability and long-term preservation of data at their organization.

By Megan Sapp Nelson, MLS

Megan Sapp Nelson is a professor of library sciences and the science and engineering data librarian at Purdue University. Her research focuses on data information literacy, teaching professional skills to engineering students, and the integration of information literacy and data information literacy within the disciplinary curricula. Contact her at

This article appears in the January-February 2020 issue of Information Outlook magazine.

No one who goes into librarianship escapes getting asked, “Did you go into librarianship because you wanted to read all of the time?” I never fail to amaze my interlocutors when I tell them I rarely work with books; rather, I work primarily with digital data. Many outside of libraries have never considered that digital data is an information asset to be managed, or that a librarian is the person who would perform that job.

Many librarians are aware that this role is emerging, but they are unsure how to get started. What skills and bodies of knowledge are necessary to provide basic services in the emerging areas of data information literacy and data management? How does an individual librarian go about getting up to speed in this area?

Data Literacy and the Changing Paradigm of Librarianship

Data literacy and data management are considered by many to be related to information literacy, a traditional purview of librarians. As such, librarians have naturally sought out and built up the literature and practice in the overlapping and inter-related areas. In the literature, data literacy (also known as data information literacy), data management and research data management involve the practice of consistent and critical skills to enable the collection of data and the maintenance of good data hygiene across the data life cycle to further the publication and sharing of data.

In essence, we seek to move traditionally library-centered practices (such as the imposition of metadata and the creation of meaningful documentation) downstream to the data creator’s computer, to enable that data to be reused in the future. We librarians have been very good at these skills for a very long time. But data literacy and data management are not limited to “traditional” library skills—they also include a host of new skills, including visualizing data, cleaning data sets, analyzing data, running repositories on servers, and any number of other highly technical skills.


While specifically developed for the academic environment, the scaffold concept could be translated into a special library or corporate library environment.


Not all librarians will have the interest, time, bandwidth, or skills to engage in these services, nor is that the expectation. Neither is it possible that all librarians will be equally engaged in data literacy instruction, given the broad range of clients many libraries serve. So how does any given librarian know how to “skill up” to an appropriate level?

Data Engagement Opportunities

The Data Engagement Opportunities Scaffold, developed jointly by Abigail Goben of the University of Illinois Chicago and this author for the ACRL Building Your Research Data Management Toolkit RoadShow, is a tool to help librarians conceptualize how they might engage in data management while simultaneously leveraging their existing strengths. The scaffold assumes that each librarian has acquired a set of skills that constitute strengths in librarianship. These skills may range from marketing to conducting reference interviews to collection development to outreach.

The Data Engagement Opportunities Scaffold builds upon the existing skills of librarians and projects them into data literacy and data management, thereby pointing the way for librarians to extend their skills base to build discrete services. Rather than attend trainings to learn generally, librarians can use this tool to discover how building up skill sets in specific areas can result in concrete service offerings. While specifically developed for the academic environment, the scaffold concept could be translated into a special library or corporate library environment, given sufficient knowledge of the strategic interests of the organization and the needs of the patron base.

The Data Engagement Opportunities Scaffold is used in one of two ways: (1) you identify a specific phase of the data life cycle that you wish to explore and then look at the skill sets relevant to that phase, or (2) you select a specific skill set you already possess and then search for potential areas of application in data literacy and research data management. Either way, you have an opportunity to identify new ways to apply your existing skills and discover potential applications of new skills should you desire to invest the time to add them to your toolkit.

Know Your Strengths

Assessing your existing strengths will help you identify areas of data literacy and data management that may be a good fit for you. For example, do you have evaluation or assessment experience? If so, you may be an ideal person to conduct data inventories, which are extended interviews with data creators that identify the data needs of individuals, the size and holdings of the data that the creators have, and the projected storage and archives needs into the future. Do you have strategic planning experience? Perhaps you belong on the task force that is determining options for long-term data storage for your institution. If you have project management skills, you may be the perfect person to head an environmental scan to determine the state of the documentation or data for a department or the institution as a whole.


No matter how you choose to invest in your skills, bear in mind that data literacy and data management are foundational skills for a data-literate society.


While each of these projects requires some knowledge of basic data literacy and technical knowledge in one or more sub-specializations of data management (such as file management, data storage, technical writing, or documentation), none require you to be an expert in all areas of data literacy and data management. At the same time, you as a librarian provide experience in information science and make a substantial contribution to the stability of data and long-term preservation of data at your organization. While no one individual needs to know all things about data management, one individual can have a marked impact on the upward trajectory of the quality of data produced at an institution.

Build Your Skills

As with learning any new disciplinary specialization, the process of learning data literacy/data management involves learning new technical information, government information, and applied technical skills. In the case of data literacy/data management, the basic data literacy skills can be acquired through online modules. The technical skills, such as file structures, naming conventions, creation of metadata, and data visualization, can be learned through tutorials and instructional video modules as well as texts. It takes discipline and extensive practice to become expert at these skills, but it is possible for an individual to move from novice to competent through independent study.

Should you decide that you want to invest your time and resources in data literacy/data management, there are a number of ways you can build your skills outside of the formal instruction environment. Goben and Raszewski have compiled a webliography of resources to assist librarians who are seeking opportunities for self-education (2015). DataOne Education Modules and the New England Collaborative Data Management Curriculum are freely available on the web and provide overviews of the foundational principles of data literacy and data management.

It is helpful to find a mentor who is an experienced data librarian. Research Data and Preservation ( is a vibrant young community of information professionals focused on the management of data. The listserv for that organization is an invaluable tool to help you both passively learn from experts and seek out mentors. It is also a place to follow to help you identify issues emerging from changing rules and regulations handed down by governments and funding agencies.

There are small regional conferences that focus on professional development for librarians who are interested in data librarianship. Look for information on data-related listservs such as RDaP or ResearchDataMan (hosted out of the U.K. Data Centre) to learn about the dates of those regional conferences.

No matter how you choose to invest in your skills, bear in mind that data literacy and data management are foundational skills for a data-literate society. Any skills you transfer to your patrons will be assets to those individuals in their data-enhanced day-to-day lives. Additionally, any skills you add to your toolkit will allow you to create data-enhanced services for your library, so there is a value-added reason to consider prioritizing data literacy skills that can move forward the strategic priorities of the library as a whole as well as help address patrons’ needs. Investing the time to add even a few data literacy and data management skills will give you more flexibility to serve the changing needs of library patrons and open opportunities for you tto innovate in your own practice.


Goben, Abigail, and Rebecca Raszewski. 2015. “Research Data Management Self-Education for Librarians: A Webliography.” Issues in Science and Technology Librarianship, Fall.
Sapp Nelson, Megan, and Abigail Goben. 2016. Data Engagement Opportunities Scaffold. Association of College and Research Libraries.

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